Lately there has been a lot of buzz around ‘predictive’ technology. Predictive technology can analyze large amounts of data so that past behavior can forecast future behavior. Let’s think of it as a cloud application that can anticipate all your needs and wishes through artificial intelligence, using previous travel habits and searches to suggest — or even book — the “perfect trip” for you.

If this was 2007, the year the first iPhone was launched, I might have said “Yes, it can be done.” At the time, the world around us was a lot more predictable. The average person would stay at the same job longer, live at the same place longer, travel to the same places for holidays and so on. The great mobile revolution had not taken off in earnest and the cost of hard drives was still high enough to act as a barrier to infinite data storage.

However, I would still not have been comfortable with the fact that we would create and confirm a travel booking just based on a computer’s assumptions —even after analysing a persons previous travel patterns and behaviours. For point to point business travel maybe (where there are more predictable behaviors as far as hotel selection and preferences), but for leisure I would have never thought so.

Why? Because travel — especially leisure travel — is an emotional and personal thing. It’s not something that most people would just leave up to a machine to decide, because travel is a complex being that is not easily broken down into repeatable, consistent and relatively universal characteristics.

Predictive technology today

Predictive technology is especially successful for commodity products with a discrete set of features. For example, Amazon was just awarded a patent for their audacious innovation called ‘anticipatory’ shipping, were they will stock certain items in different distribution hubs before they are even ordered based on this new predictive analytics algorithm, and by doing so they can keep their promise of same day delivery in more locations as the will have anticipated what items customers in a specific region are about to order. There was even a rumour that they would automatically ship an additional item from their “Other customers also bought” list. If a customer didn’t want it, they would have to send it back. Otherwise the second item was charged to the customer’s Amazon account.

I’m sure we’d all be surprised at how many customers actually keep the automatically shipped item. Customers keep these items because the effort of returning these items is greater than the reward. And in the majority of times it would actually be an item that you would consider buying anyway! That’s the power of predictive technology.

So what about predictive tech in travel?

Beyond current systems that process data to offer predictive outcomes, there’s not yet a way to book your annual vacation with one click, with an automatically populated itinerary customized by an algorithm. As I stated before, travel is an emotional thing and today there are many factors to consider in the pursuit of finding “the perfect vacation”.

This is even more true for the new generation travellers, Generation Zero (born between 1995 to 2009) as they are constantly on the go and their attention shifts at 8 second intervals. And this attention span isn’t just limited to the youngest generation; smartphones and other devices are rapidly diminishing the attention span of everyone else.

While Gen Z is constantly looking for new exciting experiences, the short attention span has empowered technology to make more of our decisions. But in travel, there are other factors besides previous trips that come into play when choosing a place to go: current weather, relationship status, present state of mind, budget, hobbies…there are many factors that determine what is the best current option for a future trip.

On top of that data, a predictive travel booking algorithm would need to have access to a searcher’s social media content (less than a couple of hours old), as well as biometric info such as heart rate to determine current state and real reactions to specific travel options. While this last bit might seem a touch much, accuracy comes from the direct tie to a searcher’s emotions.

This information would then need to be fed to some cloud based machine learning application like Microsoft Azur, and then analyzed in real-time. The computing power would need to be speedy enough to deliver that “perfect trip” in less than that 8 seconds. Otherwise, the magic is just not there! If it becomes cumbersome to let a computer decide, then the traveler will just do it herself.

The magic of travel

“Instead of trying to make a better robot, try to make a better man.”
–Shimon Peres

Knowing what technologies we have access today, I would say that this type of bookable trip with a fully automated itinerary is doable today. And predictive technology already powers much of the retailing engines that serves targeted offers to travelers — such as data-driven, customer-centric airline retailing, or the extensive algorithms used to predict air travel disruptions by airlines. In so many ways, the technology powering travel is already impressively predictive.

Despite all that, I still believe that the final decision to book a trip should always sit with a human. I truly believe that we can be successful in using predictive technology to find the most relevant options for each individual without relying only on a predictive solution that eliminates the travel planning experience. There’s still magic in travel, and it’s about using technology to enhance and amplify that inherent magic.

Joakim is the Head of Innovation and EMEA's Technology Evangelist for Sabre Travel Network. In this role, he identifies emerging trends and technologies in travel. He then follows these developments into value-add products for Sabre’s customers. Joakim is a frequent keynote speaker and panelist around mobile technology and wearable devices.